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An Initial Exploration of Tweets Associated With Web Accessibility: An Analysis of Sentiment and Readability

An Initial Exploration of Tweets Associated With Web Accessibility: An Analysis of Sentiment and Readability

Sophia Alim, Abid Ismail
Copyright: © 2022 |Volume: 11 |Issue: 1 |Pages: 22
ISSN: 2155-4196|EISSN: 2155-420X|EISBN13: 9781683182405|DOI: 10.4018/IJACDT.312848
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MLA

Alim, Sophia, and Abid Ismail. "An Initial Exploration of Tweets Associated With Web Accessibility: An Analysis of Sentiment and Readability." IJACDT vol.11, no.1 2022: pp.1-22. http://doi.org/10.4018/IJACDT.312848

APA

Alim, S. & Ismail, A. (2022). An Initial Exploration of Tweets Associated With Web Accessibility: An Analysis of Sentiment and Readability. International Journal of Art, Culture, Design, and Technology (IJACDT), 11(1), 1-22. http://doi.org/10.4018/IJACDT.312848

Chicago

Alim, Sophia, and Abid Ismail. "An Initial Exploration of Tweets Associated With Web Accessibility: An Analysis of Sentiment and Readability," International Journal of Art, Culture, Design, and Technology (IJACDT) 11, no.1: 1-22. http://doi.org/10.4018/IJACDT.312848

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Abstract

The issue of web accessibility is prevalent in society. However, few studies have looked at social interactions on Twitter associated with the issue. Sentiment analysis and readability analysis were used to assess the emotions reflected in the tweets and to determine whether the tweets were easy to understand or not. In addition, the relationship between the features of the tweets and their readability was also assessed using statistical analysis techniques. A total of 11,483 tweets associated with web accessibility were extracted and analysed using sentiment and statistical analysis. For readability analysis, 200 randomly selected tweets from the dataset were used. Sentiment analysis highlighted that overall, the tweets reflected a positive sentiment, with ‘trust' being the highest-scoring emotion. The most common words and hashtags show a focus on technology and the inclusion of various users. Readability analysis showed that the 200 selected tweets had a level of reading difficulty associated with the readability level of college students.

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